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Repository Details

In this repository, we present our research works of HKU-MaRS lab that related to SLAM

SLAM @ HKU-MaRS

1. Introduction

1.1 Introduction to HKU-MaRS lab

Welcome to the Mechatronics and Robotic Systems (MaRS) Laboratory, located in the Department of Mechanical Engineering at the prestigious University of Hong Kong (HKU). Our mission is to push the boundaries of mechatronic systems and robotics, by emphasizing practical applications that can improve human life and industry.

At MaRS Lab, our current research focuses on the design, planning, and control of aerial robots, as well as lidar-based simultaneous localization and mapping (SLAM). We believe that these technologies can have a significant impact on many fields, from search and rescue operations to agriculture and beyond.

1.2 Introduction to this repository

In this GitHub repository, we present our latest research works related to SLAM, organized chronologically by their publication date. These works showcase our team's innovative ideas, rigorous methodologies, and cutting-edge solutions in the field of robotics. We hope that our work inspires you, and we welcome collaboration and feedback from the robotics community.

1.3 Contributors (organized by letter A-Z)

1.4 Acknowledgement (TODO)

Todo

1.5 Relative Talks and seminars

2. SLAM researches @ HKU-MaRS

Loam_livox: A fast, robust, high-precision LiDAR odometry and mapping package for LiDARs of small FoV

A decentralized framework for simultaneous calibration, localization and mapping with multiple LiDARs

ikd-Tree: An Incremental K-D Tree for Robotic Applications

Balm: Bundle adjustment for lidar mapping

Fast-lio: A fast, robust lidar-inertial odometry package by tightly-coupled iterated kalman filter

Extrinsic Calibration of Multiple LiDARs of Small FoV in Targetless Environments

  • Author: Xiyuan Liu, Fu Zhang
  • Date: 2021/04
  • Accepted to RA-L2021
  • Category: LiDAR-LiDAR calibration

R2LIVE: A Robust, Real-Time, LiDAR-Inertial-Visual Tightly-Coupled State Estimator and Mapping

Pixel-level extrinsic self calibration of high resolution lidar and camera in targetless environments

Fast-lio2: Fast direct lidar-inertial odometry

R3LIVE: A Robust, Real-time, RGB-colored, LiDAR-Inertial-Visual tightly-coupled state Estimation and mapping package

Robust real-time lidar-inertial initialization

FAST-LIVO: Fast and Tightly-coupled Sparse-Direct LiDAR-Inertial-Visual Odometry

Targetless extrinsic calibration of multiple small FoV LiDARs and cameras using adaptive voxelization

  • Author: Xiyuan Liu, Chongjian Yuan, Fu Zhang
  • Date: 2022/05
  • Accepted to TIM2022
  • Github (★278): https://github.com/hku-mars/mlcc
  • Category: LiDAR-LiDAR & LiDAR-Camera calibration

Efficient and probabilistic adaptive voxel mapping for accurate online lidar odometry

R3LIVE++: A Robust, Real-time, Radiance reconstruction package with a tightly-coupled LiDAR-Inertial-Visual state Estimator

STD: Stable Triangle Descriptor for 3D place recognition

Decentralized LiDAR-inertial Swarm Odometry

  • Author: Fangcheng Zhu, Yunfan Ren, Fanze Kong, Huajie Wu, Siqi Liang, Nan Chen, Wei Xu, Fu Zhang
  • Date: 2022/09
  • Accepted to ICRA2023
  • Category: LiDAR SLAM; Multi-LiDAR fusion

Large-Scale LiDAR Consistent Mapping using Hierachical LiDAR Bundle Adjustment

  • Author: Xiyuan Liu, Zheng Liu, Fanze Kong, Fu Zhang
  • Date: 2023/03
  • Accepted to RA-L2023
  • Category: LiDAR Bundle Adjustment

Efficient and Consistent Bundle Adjustment on Lidar Point Clouds

Symbolic Representation and Toolkit Development of Iterated Error-State Extended Kalman Filters on Manifolds

ImMesh: An Immediate LiDAR Localization and Meshing Framework

Point-LIO: Robust High-Bandwidth Lidar-Inertial Odometry

  • Author: Dongjiao He, Wei Xu, Nan Chen, Fanze Kong, Chongjian Yuan, Fu Zhang
  • Date: 2023/03
  • Accepted to AIS2023
  • Github (★278): https://github.com/hku-mars/Point-LIO
  • Category: LiDAR SLAM; LiDAR-Inertial fusion

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